For computer systems to learn from experience they need information from the outside world structured in a way that is better suited to how they learn. To do so effectively, we must explore different means of representing common types of information such as images, video, sensors and text. In this course, we will explore useful ways of doing exactly that.

In this course, we will examine some practical examples of data representation as they can occur with real-world machine-learning tasks.

We will examine suitable feature representations for images, text and time series

We will develop an appreciation for the data representation challenge and the importance of giving attention to this stage of the machine learning development process.

Upon completion of this module, you will be able to Apply a range of concepts to explore different representations of data. Understand the limits and breadth of Machine Learning capabilities and Evaluate different representations of data for different purposes.